The tool FullProfAPP is framed within the European research project Battery Interface Genome – Materials Acceleration Platform (BIG-MAP), and is developed in collaboration with the Materials Science Institute of Barcelona (ICMAB-CSIC), the neutron reactor Institut Laue-Langevin (ILL) and the synchrotron ALBA.

CIC energiGUNE, the Basque research center of reference in battery storage, thermal energy solutions, and hydrogen technologies, and member of the Basque Research & Technology Alliance-BRTA, is working in the development of a software program that will automatize the processing of X ray diffraction data and will significantly accelerate its analysis, opening the door to an increase scientific discoveries. The development of this tool, named FullProfAPP, is framed within the European project BIG-MAP, led by Professor Tejs Vegge from the DTU (Technical University of Denmark).  

“The enormous quantity of the diffraction data generated by high synthesis experiments requires new software tools capable of accelerating the analysis and the processing of data, which exceed the traditional pattern to pattern analysis”, has said Montse Casas Cabanas, Coordinator of the Scientific Area of Electrochemical Storage at CIC energiGUNE. “The application of FullProfAPP in the research of battery materials will be fundamental to demonstrate their viability and their smooth extension to other fields”.

The project FullProfAPP will develop an automated tool for Rietveld analysis, applicable to powder diffraction patterns of battery materials, with which structural analysis and high-performance quantitative phase analysis will be carried out through the processing of hundreds of patterns. In order to do this, the tool will take as a basis the current version of FullProf, a well-known program for Rietveld analysis of X-ray and neutron powder diffraction data developed by Dr. Juan Rodríguez-Carvajal, and will include new routines and automatic machine learning (ML) algorithms.

CIC energiGUNE will participate in the development of the program scripts and the implementation of the ML algorithms, based on the experience acquired in the development of the refinement program FAULTS – a tool used to refine the powder X ray and neutron diffraction patterns (XRD and NPD), included in the FullProf Suite. Likewise, the Basque center will provide a big set of XRD and NPD data related to Li-ion and Na-ion chemistries for their testing.

“The launch of FullProfAPP will entail a great improvement in battery research, since it will shorten the time from data collection and its subsequent analysis, which will allow to reduce time and costs”, has reminded Dr. Casas Cabanas. Professor Vegge has emphasized that “the benefit of such programs and methods could easily be extended to other fields, increasing the visibility of the impact of the BIG-MAP project in the scientific community”.

In this project, which is part of BIG-MAP through the Stakeholder Initiative program is at the same time included in the European large scale research initiative BATTERY 2030+, CIC energiGUNE participates in consortium with the Institut Laue Langevin of Grenoble (ILL), and the Materials Science Institute of Barcelona (ICMAB-CSIC), and the ALBA synchrotron in Barcelona. The Basque center has a wide collaboration history with them, since co-developed the FAULTS program with ILL and is a regular user of the ILL reactor and the ALBA synchrotron. Likewise, Dr. Casas Cabanas actively participates in the FullProf yearly trainings at the ILL (Grenoble), and has been a member between 2017 and 2021 of the scientific committee of beamline BL-04 MSPD at ALBA synchrotron.

Furthermore, it should be remembered that a central aspect of BIG-MAP is the development of a shared European data infrastructure capable of carrying out the acquisition, management and autonomous analysis of data of all the domains of battery development. The accelerated discovery of materials with the support of autonomous synthesis modules is going to generate large quantities of DRX data -which is a technique available at a laboratory scale to identify and rapidly characterize with precision the produced crystalline phases-. “Therefore, any high-throughput approach must include tools that automatically analyze the DRX patterns of the hundreds of samples produced, and if these high-throughput efforts are linked with machine learning algorithms a great potential is opened to navigate more efficiently among the experimental spaces and to allow the autonomous experimental planning”, assures Dr. Casas Cabanas.

In this sense, the FullProfAPP tool will be designed in a flexible and extensible way so that it will be totally compatible with the BIG-MAP infrastructure, and will be openly available in the BIG-MAP App Store, contributing to the movement of “open science” and to collaborative research.

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